|
|
Absolute deviation, 绝对离差" k! Z a- {9 Q6 |7 q* t
Absolute number, 绝对数
+ g- v) @2 j8 yAbsolute residuals, 绝对残差
$ ` N! i D. o+ e+ L, mAcceleration array, 加速度立体阵
6 i B: l7 @% b. u3 zAcceleration in an arbitrary direction, 任意方向上的加速度! ?; ]# _3 S. \
Acceleration normal, 法向加速度4 j+ Z3 I! n6 c; v+ \8 _% P
Acceleration space dimension, 加速度空间的维数6 ]2 |: n( J5 A
Acceleration tangential, 切向加速度# S' m* V* V+ u# i& f( b
Acceleration vector, 加速度向量
6 I" K' v L% X9 MAcceptable hypothesis, 可接受假设
8 j$ W8 M) \* bAccumulation, 累积0 w: Z9 F4 o0 O; j
Accuracy, 准确度
! Z) _, r* y+ G+ gActual frequency, 实际频数
3 p3 X* Z: a3 m9 PAdaptive estimator, 自适应估计量6 X, o7 N/ U6 X9 }0 q \
Addition, 相加9 U p! n3 t- z0 ^5 F
Addition theorem, 加法定理+ g2 P3 R" F* I- ]1 x7 |
Additivity, 可加性1 ^/ I+ e% ]' j1 f
Adjusted rate, 调整率
' {. e H3 ~0 K( @1 Y6 yAdjusted value, 校正值
& {3 i! r* z" ]% oAdmissible error, 容许误差
4 m! a/ `, K- [; E9 a aAggregation, 聚集性" R' g7 a3 p% {; e" Y* c' X7 O" b) V
Alternative hypothesis, 备择假设
* D) L" |5 }3 M$ h) \2 ]4 dAmong groups, 组间
% ?9 J3 G3 g8 _+ I# A% e6 `Amounts, 总量
2 {# {- m6 H; |% S- SAnalysis of correlation, 相关分析
9 S# p: F/ q0 M9 h: h XAnalysis of covariance, 协方差分析1 i9 I8 E% v# d2 l4 ~8 R
Analysis of regression, 回归分析
" k9 t6 L9 X3 H9 M1 {3 oAnalysis of time series, 时间序列分析% v4 k+ c" C% v! H+ O+ N
Analysis of variance, 方差分析
& g$ ?, t+ @2 q+ LAngular transformation, 角转换+ z# v) J4 o7 M8 C+ h
ANOVA (analysis of variance), 方差分析; @; W7 B& K; `- p
ANOVA Models, 方差分析模型' U5 q+ a; q, S4 v; v6 r5 `
Arcing, 弧/弧旋1 ]7 E7 V* g) ^3 S1 p
Arcsine transformation, 反正弦变换7 z7 n9 k8 a, h3 o: c! F' l, E4 N
Area under the curve, 曲线面积; Q5 H9 a! Z3 N4 t
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 2 c, y) S0 ^& ] t4 n$ C
ARIMA, 季节和非季节性单变量模型的极大似然估计
6 B( v* g- }' d1 {$ o' bArithmetic grid paper, 算术格纸
/ {, l! R% V* i$ \' B: Z. V8 `7 QArithmetic mean, 算术平均数
! A" |) X. j( l! fArrhenius relation, 艾恩尼斯关系
) ^9 ?" ~7 J. z! V: JAssessing fit, 拟合的评估
. x7 E# z1 y6 v( a) kAssociative laws, 结合律
# S2 B L. ~& z$ z8 L5 ^, |Asymmetric distribution, 非对称分布
$ Z! U3 h: w; FAsymptotic bias, 渐近偏倚
4 l8 ~5 N0 b. L9 m9 G F4 @+ SAsymptotic efficiency, 渐近效率
0 B: X5 S5 M7 k* yAsymptotic variance, 渐近方差3 U7 Z, q. O3 D/ R' X% {( P
Attributable risk, 归因危险度 m8 r: K- {: q$ y4 s8 d4 B% _
Attribute data, 属性资料3 j2 I. n" T @( o" a+ l& Y$ v
Attribution, 属性
0 P' h& O0 n2 O9 M1 E' l# uAutocorrelation, 自相关
' G* I$ @5 N6 S8 ~# b+ ?Autocorrelation of residuals, 残差的自相关
& G5 y9 t _5 ZAverage, 平均数
. X8 N' k9 d7 ^2 a- \Average confidence interval length, 平均置信区间长度& @; K* O$ ~! e5 r, X/ t! J% M# o1 N
Average growth rate, 平均增长率
) V( X& \' ~1 L( v6 H3 \4 u3 fBar chart, 条形图
3 M, u: w- R! i+ S3 _, y% ^+ xBar graph, 条形图( J1 L1 X8 j& w3 v
Base period, 基期5 C8 s w3 D1 u2 e! O
Bayes' theorem , Bayes定理/ T1 V2 z; o5 d! D+ ?5 I" h' F
Bell-shaped curve, 钟形曲线
8 T. f; }1 o) M$ VBernoulli distribution, 伯努力分布. `3 |" V7 S( g- E, \ N
Best-trim estimator, 最好切尾估计量
5 V( ?5 Z0 b: e' D# L" OBias, 偏性
: ~3 ]9 S3 j" T& X$ B% l+ k! QBinary logistic regression, 二元逻辑斯蒂回归
# A3 C; C4 |+ |; j, KBinomial distribution, 二项分布1 s2 v" z0 w$ v$ N0 M
Bisquare, 双平方
6 F0 x+ W" K+ B: K3 z" mBivariate Correlate, 二变量相关
$ ~8 w$ K, N7 ABivariate normal distribution, 双变量正态分布
; }5 v7 d1 X6 n* hBivariate normal population, 双变量正态总体% \; r! b) t- s
Biweight interval, 双权区间
! ?0 ~* e$ H2 U& \+ `+ L( U& WBiweight M-estimator, 双权M估计量
, }1 v4 O4 h' \5 TBlock, 区组/配伍组% X n" P ^, ]) R! J* m
BMDP(Biomedical computer programs), BMDP统计软件包& Z, Z) S4 n' I8 d* l! J
Boxplots, 箱线图/箱尾图; {# a! g' K- E2 p" y: a7 m1 a) l
Breakdown bound, 崩溃界/崩溃点
7 J3 S' F d1 ]Canonical correlation, 典型相关+ F" s1 [% i+ T' X% j
Caption, 纵标目
4 Y3 z; O6 U9 a& e. N( ^8 e T& PCase-control study, 病例对照研究
$ a' p; |4 I! y% |2 e# Z+ [Categorical variable, 分类变量/ P- Q& E& R1 c; m& c2 [
Catenary, 悬链线! X1 f6 Q2 p; j2 P
Cauchy distribution, 柯西分布& B) S1 K8 J) [- n: ~! m2 t! D# p
Cause-and-effect relationship, 因果关系
9 Y& J/ w. M5 ^Cell, 单元 j G- b; a; v; H# L- d0 {9 o
Censoring, 终检
. L) g5 V* A' F" y) W, |Center of symmetry, 对称中心
% h* G9 F! u6 sCentering and scaling, 中心化和定标
6 o( G. [9 l: v9 m/ \- k" t' F# ^Central tendency, 集中趋势
9 }7 k" e1 c8 P% qCentral value, 中心值. r! Z3 k7 M& R
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
& l* r& e! ]0 F9 p8 A4 Z2 \Chance, 机遇 O, U/ u/ }+ C! v2 A, X
Chance error, 随机误差
7 l7 U$ h! A# P5 S' @Chance variable, 随机变量
8 v% H7 [* u! B) o4 lCharacteristic equation, 特征方程. `9 f2 Q4 A, c& E
Characteristic root, 特征根3 O F% b4 B7 i* Q/ b3 z2 L: _+ R
Characteristic vector, 特征向量. K( z, j7 f* k5 V8 l+ h9 |7 G
Chebshev criterion of fit, 拟合的切比雪夫准则- s+ x' ?0 |: E* j( ~2 W: w: y
Chernoff faces, 切尔诺夫脸谱图: t2 E9 p+ R' l2 ]5 [. \
Chi-square test, 卡方检验/χ2检验
' P: x9 n$ s2 h. c( P6 lCholeskey decomposition, 乔洛斯基分解4 l$ E0 u$ e7 s2 w4 ]0 r1 K5 w& E
Circle chart, 圆图
! h7 b0 ]7 ] N- P/ qClass interval, 组距- ?. T7 k# f0 s0 z! i5 o" X8 |. s
Class mid-value, 组中值
" _0 h2 M$ l1 @" N! r7 \ ]Class upper limit, 组上限7 S) ?2 Z8 A, c; k
Classified variable, 分类变量& b+ q$ D; I, z1 a P( q
Cluster analysis, 聚类分析( W% [- V9 T; y$ W3 z# w
Cluster sampling, 整群抽样
. a7 J' w# a1 a H" n! BCode, 代码
0 n$ t! y: M, h& q) f3 }9 ^! JCoded data, 编码数据) D1 m1 m0 h5 L
Coding, 编码
6 h# `- Z5 D; v: \& FCoefficient of contingency, 列联系数
" b: h8 I9 u" t% I/ rCoefficient of determination, 决定系数
% m' d* o* l* e: W$ Z# W: f4 WCoefficient of multiple correlation, 多重相关系数
! x. X" D3 p7 `& k* RCoefficient of partial correlation, 偏相关系数
5 |: V$ t1 Z) X( r6 CCoefficient of production-moment correlation, 积差相关系数" l- K. R9 w7 j
Coefficient of rank correlation, 等级相关系数
$ a* T- _7 I9 t( d9 MCoefficient of regression, 回归系数
r0 Z/ m' T4 C2 [. x2 |Coefficient of skewness, 偏度系数
! @& S8 k' U9 [8 o% K; H8 D0 xCoefficient of variation, 变异系数
4 t1 h$ X" y; b) }0 C) \& U! cCohort study, 队列研究3 e8 G! v8 d1 M" r( b
Column, 列
6 g# l0 G1 v& i. {3 \* _, A) O; i' X- qColumn effect, 列效应
- z( j" L; j0 D! }& q4 `Column factor, 列因素' U2 T' U) L9 @; K
Combination pool, 合并
2 s. \/ \8 B# m3 n2 @Combinative table, 组合表
, Z5 T1 `3 [; O1 r+ RCommon factor, 共性因子
7 Y1 v# l% e# O& {' ~5 g* JCommon regression coefficient, 公共回归系数& X& `* r% H7 `' @: [8 J, E# ?
Common value, 共同值/ m: n' o6 i4 P2 S! c
Common variance, 公共方差
7 q3 L1 {( b1 }6 t4 G8 U. }" dCommon variation, 公共变异
/ @$ l7 H' y' `$ [+ X/ HCommunality variance, 共性方差
! L7 W+ r; b2 x9 xComparability, 可比性6 i( t5 T$ T N3 ?# W; h
Comparison of bathes, 批比较
' ^( p3 \1 D: t: K- Z: l) U- ZComparison value, 比较值, O) _+ ?) q9 ^. N0 K8 o; F
Compartment model, 分部模型
' {# J, O7 J+ }7 eCompassion, 伸缩! v0 Y2 s1 W; T
Complement of an event, 补事件% V" c4 m" {7 R. p+ W
Complete association, 完全正相关
. \4 y4 H" R: pComplete dissociation, 完全不相关6 t- X) W( ]2 i) Q
Complete statistics, 完备统计量
0 A, X2 F4 v" k ?% C/ V$ \7 cCompletely randomized design, 完全随机化设计
U; S; A7 h3 a3 _9 A# o1 t5 R+ [: ]- EComposite event, 联合事件
* o7 r% w- X) c+ Y# z- B( _: SComposite events, 复合事件* ]' X# L3 U7 s! C. s
Concavity, 凹性4 q: ]8 p6 M1 f/ Y. i
Conditional expectation, 条件期望
1 f0 F% Y; f* j4 }. `; y5 U% xConditional likelihood, 条件似然 ^: ]' f3 {" Z4 i2 c2 o
Conditional probability, 条件概率
1 C1 S$ }# O: I% t4 _Conditionally linear, 依条件线性* O+ v- f4 u7 O" [$ D& r
Confidence interval, 置信区间
4 U3 ?' ~) H; z, t" [Confidence limit, 置信限+ ^6 Q7 w$ n/ t1 @% N0 y& V
Confidence lower limit, 置信下限
+ ` b" g1 l# u( C2 q' zConfidence upper limit, 置信上限. @7 m& X7 M* I
Confirmatory Factor Analysis , 验证性因子分析
; |# v: Z4 K$ H( AConfirmatory research, 证实性实验研究" T' R$ z' I" d1 s
Confounding factor, 混杂因素
% i# o+ ^ M) k! P, [/ W+ xConjoint, 联合分析
+ i4 T' B. s% N0 {9 K: ]Consistency, 相合性' ^, v s! d! k
Consistency check, 一致性检验
U+ u. a( U+ b# JConsistent asymptotically normal estimate, 相合渐近正态估计& I4 D2 r- y4 M
Consistent estimate, 相合估计
9 t" N" N0 i0 Z3 {7 k5 e( @2 TConstrained nonlinear regression, 受约束非线性回归
) L7 M( {8 s! XConstraint, 约束
' j0 J- L/ n$ o. u2 ?2 f* I: }Contaminated distribution, 污染分布
9 x& t( W- b# p; A8 r! UContaminated Gausssian, 污染高斯分布
' R# G3 R X' b9 aContaminated normal distribution, 污染正态分布
' L( U7 n& q8 w% v6 M( X8 wContamination, 污染
' x$ q- y# b0 W+ b, oContamination model, 污染模型0 @ i2 x9 H$ j2 Y" D- g9 A
Contingency table, 列联表6 a2 U$ ^4 d' N: _# F" ? G. t1 I. m
Contour, 边界线4 a3 X8 G: ~# s$ a
Contribution rate, 贡献率* S: [# {3 s1 m4 M2 Z2 ?
Control, 对照: z, W/ b' u9 }/ P7 ?
Controlled experiments, 对照实验
( ]5 E6 s; s9 G, R p/ D g, DConventional depth, 常规深度! |( B3 X& b* O6 p* T+ ]3 |" s
Convolution, 卷积$ n. h/ P& H' c" P
Corrected factor, 校正因子9 g P% m/ ~0 H# |. g
Corrected mean, 校正均值
9 ?0 |3 X' p. F' v+ E& N9 z, QCorrection coefficient, 校正系数
7 t# K: T1 C: g( \- y* qCorrectness, 正确性8 _. n7 a9 v7 B9 U) d+ q
Correlation coefficient, 相关系数
* P( c& ~: L+ f% @& m. q$ j% DCorrelation index, 相关指数 F: c* H7 \0 ]; G
Correspondence, 对应( o" ]/ }: m% [7 S3 U Y1 Z
Counting, 计数
/ J: `% f$ y* B5 e) C8 n, aCounts, 计数/频数+ V2 s+ e, c' x
Covariance, 协方差; O) A4 v. v2 l1 B& G8 Z. V
Covariant, 共变 3 M+ A0 \& G: J$ U
Cox Regression, Cox回归# E' ^$ U7 P9 f
Criteria for fitting, 拟合准则3 [" h1 }% M$ J% [# G
Criteria of least squares, 最小二乘准则* j, r- S% P* i6 _
Critical ratio, 临界比9 j; H2 a7 M, F
Critical region, 拒绝域1 L) p @6 ~ P+ ?. s; O; i
Critical value, 临界值
6 A I1 }3 U5 R# [Cross-over design, 交叉设计
8 b& d$ O5 G* r, C9 \4 a* y" V: y5 sCross-section analysis, 横断面分析6 W4 ^4 ^/ R5 u2 E
Cross-section survey, 横断面调查5 h( S- ^0 f C) s0 v
Crosstabs , 交叉表
, s! W$ y- L9 U$ y0 s S3 mCross-tabulation table, 复合表$ {" D! B/ v l1 Z. ^2 H' j6 T
Cube root, 立方根
: o5 i# }( F: t* O4 S. d: g% p% o% H: SCumulative distribution function, 分布函数
$ E$ ?5 P4 [6 a0 KCumulative probability, 累计概率7 |' ?- ~, A0 z$ [0 R/ U
Curvature, 曲率/弯曲
( {0 q. s- t! j+ p2 iCurvature, 曲率5 }) v3 M! z7 {; a+ x2 ?
Curve fit , 曲线拟和
8 x9 Q8 S, ~3 M# tCurve fitting, 曲线拟合+ T0 ]* N/ q, r' r
Curvilinear regression, 曲线回归5 x. L7 p2 J1 C- Y0 ?
Curvilinear relation, 曲线关系$ V H' Q0 G! K, b7 B$ d' `
Cut-and-try method, 尝试法
; |# n% S1 j# ]/ E& k# W* DCycle, 周期% u" w6 O4 E$ F w* [
Cyclist, 周期性, b H0 v6 U2 B% u" K9 R7 ~
D test, D检验
5 N) R1 q6 {; |Data acquisition, 资料收集; R0 \3 t6 B; D* ~1 G, |9 R
Data bank, 数据库. _! M, l+ N7 k, Q- C9 }2 L2 K6 b
Data capacity, 数据容量( F, ~. F6 j' }, M9 n
Data deficiencies, 数据缺乏! v3 u6 ?" `% }7 g3 _. u1 s: l1 L
Data handling, 数据处理( T/ D' A" G; T: s* U1 k0 I/ t- L9 \ t
Data manipulation, 数据处理1 r7 y; ]( ~) p, N; C
Data processing, 数据处理( H( G4 w8 l2 S
Data reduction, 数据缩减
0 [1 S$ n1 R! w5 ?Data set, 数据集
4 s: L5 P6 q. AData sources, 数据来源
* m- ?% }" h$ k z; L" xData transformation, 数据变换
. y+ r, i; a- U3 C. B5 H1 eData validity, 数据有效性
& o+ T. h; g2 }: {Data-in, 数据输入) R7 l) \% |& t K; V
Data-out, 数据输出
4 U& z: b) C; J/ E4 Y g5 ODead time, 停滞期
+ i# E, U4 @! r$ ODegree of freedom, 自由度- u) n4 `- s( g; y7 e- r
Degree of precision, 精密度
( e6 O% G2 {( h! e$ z6 s- ~Degree of reliability, 可靠性程度
% o: Y0 j7 p9 f) WDegression, 递减3 P6 A7 m F/ z. [1 {! R( l
Density function, 密度函数
) A+ H$ f7 w4 VDensity of data points, 数据点的密度
7 Z6 F8 N( x. ]5 iDependent variable, 应变量/依变量/因变量& |$ p; C% }& s1 S) r
Dependent variable, 因变量
7 A( |8 ?$ T4 j, U4 m2 y: zDepth, 深度" i6 I0 }7 Z1 b0 S* S
Derivative matrix, 导数矩阵
; ~( {# d n" f; o8 j# |) gDerivative-free methods, 无导数方法
/ }) N! O- j% l; _% tDesign, 设计
6 X8 o" N# S1 I0 l9 _1 Y EDeterminacy, 确定性1 U" n( ]' J4 p6 c3 @1 w
Determinant, 行列式
: @9 q$ d6 ^% w7 F/ R& {5 M: hDeterminant, 决定因素3 u& G; i) ~; F2 ]
Deviation, 离差 a6 |6 K8 e7 j' ?5 L" B
Deviation from average, 离均差
J/ N- B, @* e, ]; _/ E& `" vDiagnostic plot, 诊断图
8 C& \. P, g p! X* w; z. }Dichotomous variable, 二分变量
: [# Z+ ~6 {4 p6 h% ODifferential equation, 微分方程
8 H, t6 J, |1 e* ^* Z- NDirect standardization, 直接标准化法2 K0 Z( `3 b4 x% I6 ^, e2 K/ R" }5 @- y) o
Discrete variable, 离散型变量; \ ]3 e8 h) D5 U. R" {$ Q
DISCRIMINANT, 判断 + I" m& Y3 Y, X4 r# N0 L- V3 m
Discriminant analysis, 判别分析
y/ _+ |6 D5 ]) h* e9 oDiscriminant coefficient, 判别系数9 ^2 R' k! N+ E. r+ E) j) N/ N
Discriminant function, 判别值$ @" k& f* b( Z% V d
Dispersion, 散布/分散度: X \8 _4 z( L
Disproportional, 不成比例的
& r8 y4 \& ^$ r4 g( I4 V* ?Disproportionate sub-class numbers, 不成比例次级组含量6 W# Y9 Q, p+ x# q8 @
Distribution free, 分布无关性/免分布
& ?8 m6 t& o8 v8 }6 YDistribution shape, 分布形状3 U2 Z% U/ ]) H
Distribution-free method, 任意分布法9 i! v6 p& `- X% d2 `6 J) G; N+ ?
Distributive laws, 分配律3 e( t6 L, P: b) t3 a' V/ J; x" B
Disturbance, 随机扰动项) ^" ]: l- w4 i& Z+ k4 }- O5 G
Dose response curve, 剂量反应曲线
8 b7 {8 n* J) E' YDouble blind method, 双盲法& ~5 A5 r7 x- b, [
Double blind trial, 双盲试验& ]3 G/ r6 E/ z/ d2 A2 f
Double exponential distribution, 双指数分布7 u \* N7 ]. R O
Double logarithmic, 双对数- j5 a( h* B- T0 q
Downward rank, 降秩- S _# w# t% A3 n4 y6 ?0 A
Dual-space plot, 对偶空间图' X; i# V/ O c
DUD, 无导数方法
( c* Y# D* t8 d @Duncan's new multiple range method, 新复极差法/Duncan新法
9 w2 j0 a5 I1 t# _' _Effect, 实验效应4 S& |# {+ w* y4 K) n% [
Eigenvalue, 特征值
% L6 p [6 U. ^9 y5 HEigenvector, 特征向量
% ~' u. F! J: q* B) {Ellipse, 椭圆' m& U1 Q& d1 @. w2 g
Empirical distribution, 经验分布: K, q) _$ N9 ~6 ]8 C; b* W
Empirical probability, 经验概率单位' C) [ W7 c8 ]* K* S( ~6 ?9 ^3 S
Enumeration data, 计数资料$ U a4 }8 x2 L( y
Equal sun-class number, 相等次级组含量" g% v4 i4 m, u5 Q
Equally likely, 等可能
" F/ P" w! w; D1 R Q' pEquivariance, 同变性' X2 `0 `/ X X" b% u1 K
Error, 误差/错误& K# Z3 Z5 ]3 B, D: ~! M
Error of estimate, 估计误差, M3 p" V, x! I. v( y
Error type I, 第一类错误
; ?5 O; B! J& c. ]Error type II, 第二类错误
7 q8 U5 }; w3 M( nEstimand, 被估量
3 z$ a# Y7 z: \$ r; MEstimated error mean squares, 估计误差均方
4 O4 \' \! X$ M" A- W0 ], G# gEstimated error sum of squares, 估计误差平方和
: f! U! C/ ?& u! Q7 DEuclidean distance, 欧式距离
6 h- K) W" {0 q. ?& oEvent, 事件
& H- H7 W9 Y2 q* k: vEvent, 事件
4 B6 t" g2 C, X5 ]; [' B, nExceptional data point, 异常数据点
, \! K$ S' W+ Y3 JExpectation plane, 期望平面
! q1 F0 I- ^% n8 E: h+ ]Expectation surface, 期望曲面+ p _ [# q# d* l) [
Expected values, 期望值4 n; h7 S0 ^6 G
Experiment, 实验0 j3 [, L1 K5 G$ Z
Experimental sampling, 试验抽样
! L, c. Q" H# r$ U! C. j' qExperimental unit, 试验单位
" g4 D; R8 ^$ t( O7 kExplanatory variable, 说明变量1 d7 Q& ~0 I' _( r
Exploratory data analysis, 探索性数据分析2 F# G6 z3 ~9 t/ z+ p7 Q
Explore Summarize, 探索-摘要5 D' _* h7 S" g: V1 q. l. `
Exponential curve, 指数曲线6 C& V i. w! B2 {) d! O
Exponential growth, 指数式增长3 S& ^( G! F5 B! A; i& ?7 m! S3 C
EXSMOOTH, 指数平滑方法
& T ^! v( y9 y5 @4 MExtended fit, 扩充拟合
7 T; E) H7 Y+ F2 F1 B# f0 wExtra parameter, 附加参数
" C3 k( o" c2 }% j- z- V" dExtrapolation, 外推法0 m; ?3 {. Q7 w& i7 U# c
Extreme observation, 末端观测值
' g% q' \2 n1 I R% Q- g7 @Extremes, 极端值/极值
& p+ F& u; z4 z3 u& V) tF distribution, F分布; H, }) p! [6 u/ }
F test, F检验
9 I+ N( @5 `) f+ s" jFactor, 因素/因子: y- c- U; _; X8 B- }
Factor analysis, 因子分析7 {0 d4 b; ^+ L8 B6 g
Factor Analysis, 因子分析
e4 r+ c8 A! L' BFactor score, 因子得分
! I6 n- W( G; g" @Factorial, 阶乘
3 W/ x/ {1 `+ E9 \6 c: l6 \# ZFactorial design, 析因试验设计3 V U( l1 h& M! H
False negative, 假阴性
5 [3 }" L$ i5 Q* a7 n5 X; F! }False negative error, 假阴性错误0 Q. \2 X$ a% m9 J# `
Family of distributions, 分布族1 p0 f5 n; i- w4 L5 v9 L" D
Family of estimators, 估计量族
8 u1 X' q7 B' j* C" }! V7 e: P$ bFanning, 扇面3 g7 W! ~, {$ M9 Z, k
Fatality rate, 病死率
) Z" B/ {5 z, _ p/ oField investigation, 现场调查5 i8 h+ o* o' W) H0 k
Field survey, 现场调查
0 A- n3 U# n0 v2 R/ j8 v- Y" cFinite population, 有限总体5 T6 V+ s4 `2 r- M7 K* Q; S# v
Finite-sample, 有限样本 \6 L3 ^4 M* g- T) t. H
First derivative, 一阶导数# U0 ~+ I X% X) K8 r2 P2 Z
First principal component, 第一主成分
0 d* P/ a* D0 L! Z) H7 t! ]First quartile, 第一四分位数, ~+ Q8 P. W% }5 H4 Y
Fisher information, 费雪信息量
/ u8 D" ]) [9 Q1 K2 y% s$ yFitted value, 拟合值) m! C0 d9 H* ]: P$ g) i8 D) W
Fitting a curve, 曲线拟合
, M0 s4 _; t- ^4 ~Fixed base, 定基# P) W) p- i; i8 K
Fluctuation, 随机起伏
, g2 ?5 L. f& V7 c9 aForecast, 预测* |: `2 O& M# Y- C- N( b
Four fold table, 四格表! J" b+ h4 e9 T) x2 p: z9 x" p) ]) @
Fourth, 四分点1 A u5 e0 M0 B N5 x7 B3 c0 _ h
Fraction blow, 左侧比率
+ _0 O/ i+ v' e" JFractional error, 相对误差& v* ^- C& l$ p! j p3 n
Frequency, 频率
. x& M, ~& {* v) `( n) T7 z$ w4 iFrequency polygon, 频数多边图
# o- m% U" K% V4 n5 F% w# XFrontier point, 界限点
9 `7 V( N- B+ T5 DFunction relationship, 泛函关系; T! R7 E. m+ r4 W7 e( ~1 [
Gamma distribution, 伽玛分布0 C1 [0 ?* B! s9 k2 F
Gauss increment, 高斯增量! L; { a" n+ Y& G+ M) g% X& j7 ]# g
Gaussian distribution, 高斯分布/正态分布, y4 J i: ^# x0 l3 l5 Q8 C2 K
Gauss-Newton increment, 高斯-牛顿增量' S3 Q1 s! o1 y! {
General census, 全面普查
& R W l% h% \ j3 i- AGENLOG (Generalized liner models), 广义线性模型
- ~: M; T. n- K7 u- e7 x6 AGeometric mean, 几何平均数
" M1 Q2 X' B% h% QGini's mean difference, 基尼均差
2 p3 s3 D, Z( q5 aGLM (General liner models), 一般线性模型
6 Y/ ]1 e! I' y7 L7 T4 aGoodness of fit, 拟和优度/配合度9 t" i& G7 ?" u1 D1 W& ]
Gradient of determinant, 行列式的梯度& z8 ~$ D2 V; H- q
Graeco-Latin square, 希腊拉丁方( @ q2 A& X7 n4 a$ d
Grand mean, 总均值; d/ C) K, ]5 G, i8 A3 n; J
Gross errors, 重大错误
, @/ R+ i' A, O) D/ LGross-error sensitivity, 大错敏感度
@- | d8 p- Q* EGroup averages, 分组平均
/ J2 r4 {2 b# \+ [Grouped data, 分组资料
7 g$ _' p" k7 zGuessed mean, 假定平均数
/ d. ^( b( ]4 D, Q9 g* nHalf-life, 半衰期$ |! r8 d9 V/ a5 _! S" \
Hampel M-estimators, 汉佩尔M估计量
/ d8 V! \- X. S; R/ ZHappenstance, 偶然事件, K- v, a" [# a# e! B; M
Harmonic mean, 调和均数
3 a2 G! x$ R4 f3 Y* PHazard function, 风险均数( p. y7 {6 n& u8 Q6 c \1 K7 Z# |; |
Hazard rate, 风险率
, i, N, B5 @5 j F* {3 m1 w& gHeading, 标目
4 Q2 T$ i+ [( D+ N, s0 cHeavy-tailed distribution, 重尾分布
& x: d$ q# x6 L! P; `Hessian array, 海森立体阵) }5 R! m3 N6 n4 k- G5 @! G
Heterogeneity, 不同质
8 r0 z% c& g1 c/ d) UHeterogeneity of variance, 方差不齐
* d8 x1 m7 o* |0 ~6 p8 wHierarchical classification, 组内分组
; s# T) u( a0 _+ P- @, SHierarchical clustering method, 系统聚类法; h j* v$ k0 L4 I! t
High-leverage point, 高杠杆率点
: c- Z& v9 t5 {1 M2 U! G) Q/ n0 ~HILOGLINEAR, 多维列联表的层次对数线性模型
/ M& _8 P" l. f e6 J. XHinge, 折叶点
; F" w9 N9 P6 l1 n8 e3 ^' lHistogram, 直方图
) ?7 ]1 D" s7 S% l/ j( Q9 D5 OHistorical cohort study, 历史性队列研究
6 J8 |- }% s8 f' x! i7 WHoles, 空洞
0 W, U: e3 [% x1 NHOMALS, 多重响应分析5 |" M4 ?. m8 k1 s
Homogeneity of variance, 方差齐性/ P5 |' _4 {+ l# p! G
Homogeneity test, 齐性检验
3 k' m& ~. u: A) j/ `Huber M-estimators, 休伯M估计量
+ ^) w: N7 A. s6 M' B& q0 cHyperbola, 双曲线& F1 z6 O3 R0 k' B! N1 F
Hypothesis testing, 假设检验: B4 N& f- x$ s( _! {# H
Hypothetical universe, 假设总体
, X1 |$ [! t) I9 ]2 FImpossible event, 不可能事件1 V1 H2 g) J: t! |: M7 F% I
Independence, 独立性
+ {2 E2 H( v6 f( L2 OIndependent variable, 自变量$ \: Y! x0 z7 A& F9 c% @
Index, 指标/指数; X5 i- p9 h4 i. Y6 j2 A
Indirect standardization, 间接标准化法8 W# O, K1 B$ f8 T
Individual, 个体
( A3 B2 c' K' @& I, o. O; R8 h$ C6 DInference band, 推断带
* X) a) h1 M3 M/ PInfinite population, 无限总体
8 \9 m& r, o/ w; x8 A- fInfinitely great, 无穷大
& l j% A' f5 q6 jInfinitely small, 无穷小
# D0 R6 w- L; R. yInfluence curve, 影响曲线
& [- c$ X, |) \5 qInformation capacity, 信息容量6 ?/ g3 R9 @1 z8 ]6 W8 [2 r' `
Initial condition, 初始条件: p/ U7 A6 X$ o2 d1 R8 b* |
Initial estimate, 初始估计值
; r. H& c: d8 @5 m" N0 B( S4 UInitial level, 最初水平
1 i) b$ @" f2 w! M8 FInteraction, 交互作用
! }3 ~4 e G- K+ J* MInteraction terms, 交互作用项& [& G$ {3 ~) O: }0 e' O" M- d& {# [
Intercept, 截距
4 P2 B" W* Q3 P4 V! j+ \Interpolation, 内插法2 t. k7 x( d5 ~; }
Interquartile range, 四分位距
1 x3 ^) g3 E/ \* n1 O' R) }Interval estimation, 区间估计
8 M5 `) L9 x9 v1 N/ m* h; d: wIntervals of equal probability, 等概率区间
+ v6 t( F3 ^- r8 `4 ~+ aIntrinsic curvature, 固有曲率7 x `+ n$ J# K3 y. K
Invariance, 不变性
, w: D5 f9 C0 C4 R/ @6 c$ x" ~Inverse matrix, 逆矩阵3 y9 B2 c& A) l/ k c9 p
Inverse probability, 逆概率# u, p% ^9 C' U/ [; s, W8 P% S
Inverse sine transformation, 反正弦变换. C) V% y) n1 @
Iteration, 迭代
# N7 H B/ C5 H; J+ s9 @Jacobian determinant, 雅可比行列式
" Q' _9 a. `( r& C9 U/ nJoint distribution function, 分布函数1 Q! l5 \9 y% @; R! B; {5 C9 i: X
Joint probability, 联合概率
9 y6 P r$ e. j2 u% v, TJoint probability distribution, 联合概率分布
* w9 E9 W' Z! a" }5 ZK means method, 逐步聚类法* m6 A, @) N2 d" N! Q0 w( d* ^
Kaplan-Meier, 评估事件的时间长度 1 b- g8 O0 z" ?) ^( ?# z3 U! r
Kaplan-Merier chart, Kaplan-Merier图
: Q, C6 g7 E( t3 mKendall's rank correlation, Kendall等级相关
, D0 v3 x1 Z$ D! i$ ^* Y2 }Kinetic, 动力学
s' F% r4 ~8 |% TKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验8 A; m ~, F; [$ {7 L
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
8 N, z4 [$ q% \3 y/ @8 VKurtosis, 峰度
0 z5 ~& A0 U/ {( s lLack of fit, 失拟; z, P9 ?$ F. u/ Y" k
Ladder of powers, 幂阶梯1 K2 Z$ s+ ]) B
Lag, 滞后3 B# |2 i* s0 X
Large sample, 大样本* G4 r0 B3 D; C
Large sample test, 大样本检验
4 A8 ?2 Z8 L4 u! o. PLatin square, 拉丁方1 d4 m" Q1 ]5 k9 z7 o# P! r- {$ K
Latin square design, 拉丁方设计 v! }6 u4 d% B
Leakage, 泄漏6 o0 l& l& s" Y- Z
Least favorable configuration, 最不利构形! F3 ?! h0 n+ n4 _7 X2 r
Least favorable distribution, 最不利分布
[4 K; z/ H e+ k2 zLeast significant difference, 最小显著差法$ X) s/ Z5 h* x' K
Least square method, 最小二乘法
/ i/ ?: I1 q4 w- ^9 I0 L: cLeast-absolute-residuals estimates, 最小绝对残差估计9 x) a( N, p: @2 F% @: D
Least-absolute-residuals fit, 最小绝对残差拟合7 u* j. x J% F- ~/ p; J* {
Least-absolute-residuals line, 最小绝对残差线
* V, D/ G2 {% m, C4 f+ ]" T' gLegend, 图例
9 z& X5 x- C: h& W. Y1 @L-estimator, L估计量
( n4 E3 Y/ q9 s5 o, q+ i) ^L-estimator of location, 位置L估计量2 W; \' v: x; [
L-estimator of scale, 尺度L估计量+ k" V, d5 B* S3 p5 X
Level, 水平
& j4 m& T" I: |Life expectance, 预期期望寿命# \- Q. J! G! y
Life table, 寿命表
" _8 @# ]# D) _; Z1 FLife table method, 生命表法% y1 g0 c% g, _" b
Light-tailed distribution, 轻尾分布5 |0 c. d& @4 U8 e
Likelihood function, 似然函数
7 `2 ~! [$ ~6 U5 VLikelihood ratio, 似然比: f+ D2 H# |6 t$ Q! q
line graph, 线图) z0 n& X8 P+ z" [5 R9 \( J9 I
Linear correlation, 直线相关: c% w$ }+ m/ N- I5 @
Linear equation, 线性方程
, I! {* g% g. O) t" }/ k6 jLinear programming, 线性规划
3 N! W# Y: u" gLinear regression, 直线回归
. M4 S% a8 n; P* ?1 ZLinear Regression, 线性回归
9 K7 w) E* `; q- d$ T: p! t! \Linear trend, 线性趋势
. c, x9 D9 l' e6 z9 ^* L: p: zLoading, 载荷 ! m% U1 M3 R7 ?! {: _
Location and scale equivariance, 位置尺度同变性+ ?* I/ i: G# k3 z \
Location equivariance, 位置同变性; l1 F1 X) J0 W. J! H$ M/ ]
Location invariance, 位置不变性
+ A; [$ v( q3 S: xLocation scale family, 位置尺度族8 I( ~* I6 J& _. g
Log rank test, 时序检验
* B/ J; I5 k* H( F- A8 c& u o# kLogarithmic curve, 对数曲线
9 K0 A$ Y3 c1 s, T3 R) \! gLogarithmic normal distribution, 对数正态分布
, T& m+ {$ R2 p8 E3 CLogarithmic scale, 对数尺度
) v& M* G) | G9 R9 S8 y, J NLogarithmic transformation, 对数变换9 z" Z& P* k/ _4 {
Logic check, 逻辑检查
4 T$ w3 ~3 F8 G1 aLogistic distribution, 逻辑斯特分布
: F/ J( p! y# {; m4 XLogit transformation, Logit转换
5 X* D4 c& n7 q. {# `LOGLINEAR, 多维列联表通用模型 , U( q+ T q9 t( ?1 N2 d+ x
Lognormal distribution, 对数正态分布' g: @% `# ? \. Q7 f& [
Lost function, 损失函数
) S4 T$ T R; h5 H! U, rLow correlation, 低度相关: y3 K: e, k( B S1 z, R1 w
Lower limit, 下限5 {! N3 g- ~9 M3 i
Lowest-attained variance, 最小可达方差
& n. @# h |! i8 V1 Q% |LSD, 最小显著差法的简称
" b: v9 d4 T" @/ Q& D( bLurking variable, 潜在变量
$ V6 b3 `9 h) n, J- eMain effect, 主效应7 p: `) U# w# ~
Major heading, 主辞标目5 {6 |0 x5 M/ |' \
Marginal density function, 边缘密度函数4 t% x8 E6 E- G# E$ X5 @& U% `+ Z
Marginal probability, 边缘概率
6 v8 z+ Z7 ]7 f! y6 i4 b/ c0 qMarginal probability distribution, 边缘概率分布3 M% G6 p1 A4 H
Matched data, 配对资料
0 S- h8 x$ y6 N( K/ k: A, pMatched distribution, 匹配过分布1 B) V3 L# [0 L3 \4 E7 w
Matching of distribution, 分布的匹配
/ ?8 _ j; i' \- e9 c2 t% fMatching of transformation, 变换的匹配
( N+ b. g/ ?3 I; d( }$ I; p+ QMathematical expectation, 数学期望
( J+ }( Y1 B! E+ I) d, w' O6 `! qMathematical model, 数学模型& I3 t9 Y/ r3 E
Maximum L-estimator, 极大极小L 估计量/ U9 f0 y4 U4 E5 i1 }
Maximum likelihood method, 最大似然法5 f' A K5 ~; P# Q* ^+ j8 \
Mean, 均数
) _: J4 [0 E: a LMean squares between groups, 组间均方
) l. I$ y" ?/ h( p, FMean squares within group, 组内均方) m! O m% E2 [# N6 e" n* K
Means (Compare means), 均值-均值比较* D. w7 z' w; F: U7 U5 f4 y6 O
Median, 中位数
! b: f, y5 d, X5 I+ U: l& QMedian effective dose, 半数效量
5 _+ o+ C# h! R% ]0 o* X) j9 RMedian lethal dose, 半数致死量: j7 d- L4 c; t2 T& q m
Median polish, 中位数平滑
; v4 {: ]: H, SMedian test, 中位数检验1 i, q, H# t+ V! a" D5 H
Minimal sufficient statistic, 最小充分统计量/ O( F% U- H: H" K
Minimum distance estimation, 最小距离估计
5 ~5 h# h& j v1 q, F; iMinimum effective dose, 最小有效量# Q" j1 Y$ g, P1 b# U; P7 V8 g
Minimum lethal dose, 最小致死量
4 c( r4 t! o, R8 I. c A6 YMinimum variance estimator, 最小方差估计量
) {( A$ @$ l) P) x& }9 xMINITAB, 统计软件包
9 z8 J; x. O% B/ u/ S' n6 N, iMinor heading, 宾词标目
0 ^" W, S. I9 \, v3 Q& ^2 @7 i6 GMissing data, 缺失值
7 ^* }. ?7 {4 R' yModel specification, 模型的确定' `# ?: q! Q( x! s
Modeling Statistics , 模型统计, d! C; ^ }6 N* ]; u. i- `
Models for outliers, 离群值模型# G! m: i8 p9 S6 X3 g/ X
Modifying the model, 模型的修正
- t% q8 H9 S" z: q1 V5 dModulus of continuity, 连续性模( V6 b3 i& A0 I/ p0 w. X% f
Morbidity, 发病率
# `0 ]6 S+ T% ^& ]$ V+ Q" T, IMost favorable configuration, 最有利构形; q6 y. Y( ?3 W* T- A
Multidimensional Scaling (ASCAL), 多维尺度/多维标度; K4 D, n6 i# E! e# |
Multinomial Logistic Regression , 多项逻辑斯蒂回归
) c: C% G. R0 `' u+ f6 G" TMultiple comparison, 多重比较; t" c& n; L! Y2 S1 ]; W5 z
Multiple correlation , 复相关+ \ b5 S0 W) v- `' ~. b
Multiple covariance, 多元协方差
& p+ q+ w( U7 |7 \( TMultiple linear regression, 多元线性回归, g! C0 y$ i; j" k4 B: x
Multiple response , 多重选项2 {* g! @/ [9 I% ~, o7 Y$ v' j8 \
Multiple solutions, 多解
: X4 L% F, ~: n0 lMultiplication theorem, 乘法定理
8 b( |; e+ @) a$ ?( r/ X% \' ~Multiresponse, 多元响应0 K9 A& R) C; N5 n2 m
Multi-stage sampling, 多阶段抽样) n- V1 k5 q& j8 Q% z4 }
Multivariate T distribution, 多元T分布) J1 \ O; X5 X. ]
Mutual exclusive, 互不相容1 ?/ l2 b$ g# a$ h
Mutual independence, 互相独立, @) Z- z/ ^/ g9 P/ c" v# }
Natural boundary, 自然边界
' A+ q; a1 Y$ W5 C& L0 _Natural dead, 自然死亡
. u+ |1 T# E3 C& b o4 j5 D$ h/ A$ B3 hNatural zero, 自然零' c5 |( I# G: E/ a0 w6 m
Negative correlation, 负相关
' Z& C7 K9 w4 O+ ?Negative linear correlation, 负线性相关2 k+ @$ v/ s. n" E/ J6 a& d1 G5 p
Negatively skewed, 负偏( y) D4 ?" T1 {* N$ l. a
Newman-Keuls method, q检验# q8 o5 X; \% M% s# e7 ^
NK method, q检验' {% j5 ~# v. P3 K3 R m
No statistical significance, 无统计意义7 v: I" G7 L4 s5 x
Nominal variable, 名义变量! u' k, B- k' W
Nonconstancy of variability, 变异的非定常性* }4 a7 c C* v
Nonlinear regression, 非线性相关7 v( L! W) j( K9 Q' K
Nonparametric statistics, 非参数统计( B/ m: m; a& G( Q7 h# x/ o; N
Nonparametric test, 非参数检验
6 p }! |) D$ i( sNonparametric tests, 非参数检验
6 M0 L' v" W, ~% Y4 B: I8 ? P0 f# ^Normal deviate, 正态离差; I# E2 t, K, w+ |
Normal distribution, 正态分布
% Z7 q- ^; {. L! O# z# J: v. zNormal equation, 正规方程组, d! d' k% r4 @/ g) m& C; W
Normal ranges, 正常范围8 t' o# ?4 D4 I
Normal value, 正常值
3 ]9 a. @" Z# m" b2 B2 r/ v/ M" w4 q$ B8 kNuisance parameter, 多余参数/讨厌参数! e9 {. `3 p9 K- o' L( V4 s" \
Null hypothesis, 无效假设
|2 ~9 }' z- A) VNumerical variable, 数值变量+ M/ u5 r) K2 \
Objective function, 目标函数
% \' M+ R m' c. H% TObservation unit, 观察单位! h% _8 y) k9 `
Observed value, 观察值
1 t0 ?% _. I, A) w' ^" F! z: DOne sided test, 单侧检验
( p [0 X1 d/ U/ z& p' h/ sOne-way analysis of variance, 单因素方差分析
! Y) H s$ A- y; aOneway ANOVA , 单因素方差分析! b, V; @ r" f% B4 _) d4 @& T0 \* q
Open sequential trial, 开放型序贯设计
$ H! f G5 M$ Q8 r$ t: a! A! fOptrim, 优切尾! n \" A5 {4 R: T8 Y+ ?
Optrim efficiency, 优切尾效率
6 |! X! s6 [+ K$ ]: E# }. e7 C' JOrder statistics, 顺序统计量* @) M/ \3 q! c0 ? n1 p7 F5 X' S% d
Ordered categories, 有序分类
1 }7 N2 G- j6 p8 M5 L3 G) QOrdinal logistic regression , 序数逻辑斯蒂回归
$ r* B2 u& q& k: A/ \* eOrdinal variable, 有序变量5 q; F+ g1 O- P; O* ?( m' v# m/ [3 p
Orthogonal basis, 正交基
# o% c) K; }' ]Orthogonal design, 正交试验设计
" X \6 h% t5 R" U/ ]* [3 e+ ^! ]Orthogonality conditions, 正交条件+ @7 q) `' C7 m% F
ORTHOPLAN, 正交设计
/ `0 S5 }" S9 N/ U& J+ w! rOutlier cutoffs, 离群值截断点, \3 o& w7 e+ J- }3 r! f# B
Outliers, 极端值: g Y( C/ ^# \" ], G7 t
OVERALS , 多组变量的非线性正规相关
1 m* ~( \+ n p& Q3 }/ ] o. h& |# ^Overshoot, 迭代过度. J8 ^# h5 @& D! _9 A- [
Paired design, 配对设计2 c8 [( ^0 |$ U* p( `: ]2 ~
Paired sample, 配对样本
: t* c7 W. Z/ @9 ~5 K. B' yPairwise slopes, 成对斜率& s% I5 u$ t3 F/ A3 d) H/ V# p L
Parabola, 抛物线
1 }8 }+ a2 ]9 c3 K/ E6 wParallel tests, 平行试验$ [: G! n- Q8 J1 ^+ {3 U
Parameter, 参数; L! i7 x4 T( i, h4 d" r
Parametric statistics, 参数统计4 C7 C, v8 E% O; Y
Parametric test, 参数检验! a- {/ I' S6 O7 y
Partial correlation, 偏相关
- J. R- ~* b* X0 Q( b6 OPartial regression, 偏回归# t; A U) k6 {; b+ N
Partial sorting, 偏排序
Y6 V3 D; j' q2 c% j/ |Partials residuals, 偏残差2 w9 }1 o2 f& V$ @3 m* \8 T
Pattern, 模式
$ ~* y9 F' A2 ^. a d' E& xPearson curves, 皮尔逊曲线
6 y* M5 q' f; n" E+ ePeeling, 退层 H% I/ @- `& e% D, M+ W" u& |
Percent bar graph, 百分条形图
, I* `: U4 {2 o# y/ UPercentage, 百分比 U* p0 @* X) J+ c) L
Percentile, 百分位数
- k1 Y* q! D, K) X+ S- G8 l8 z( Q% `Percentile curves, 百分位曲线- S3 |! g) b4 r- y8 ^. @
Periodicity, 周期性" \6 K2 ^( l$ E
Permutation, 排列
7 f; }, T+ ?) Y, ?& DP-estimator, P估计量
5 U% a/ W6 L$ f" O4 q7 I$ iPie graph, 饼图$ ^5 D0 }7 ~/ Q6 [7 C1 F
Pitman estimator, 皮特曼估计量4 F3 w& Q2 v5 s( G( f8 O9 u% U! c3 g
Pivot, 枢轴量# O) U p1 X& [# a6 x& Q. \ ~
Planar, 平坦; u/ d1 H) o) X: N* G" S8 r
Planar assumption, 平面的假设( e* I& Y* _! t: h1 r# e. j
PLANCARDS, 生成试验的计划卡: M1 ]# ]5 j/ i# \* [1 |, g- K# G
Point estimation, 点估计& X' m1 D$ e6 d+ I7 t* Q3 x
Poisson distribution, 泊松分布- C+ x# _6 t, k: S+ f* x
Polishing, 平滑
2 l8 c0 ]* I9 e; u! N6 OPolled standard deviation, 合并标准差
+ T' T/ A/ f( H: KPolled variance, 合并方差
" b/ L3 X, t5 t" S$ VPolygon, 多边图
! x* ~, z/ A. I" Y _3 \+ l5 {Polynomial, 多项式
( N0 b, C/ N- _. |Polynomial curve, 多项式曲线9 C. z# L7 t3 D: F. ?+ ^
Population, 总体0 I# }: |/ t; x; v' r
Population attributable risk, 人群归因危险度
6 }5 Y3 K1 U7 ]Positive correlation, 正相关
* A3 t# L+ W+ U$ G# B$ k+ EPositively skewed, 正偏
1 ]1 b9 c1 G; V& GPosterior distribution, 后验分布
, K8 A) ]8 R3 H8 WPower of a test, 检验效能# `" G5 k/ H9 z( z
Precision, 精密度
: v+ S) N3 U) V" h# d5 U! gPredicted value, 预测值4 ]% F `! P- p2 a
Preliminary analysis, 预备性分析" H: ~; t7 ^9 V. \; e
Principal component analysis, 主成分分析
/ b# L# [* z( T; p7 vPrior distribution, 先验分布
6 G7 f% l; R2 }Prior probability, 先验概率% w5 s! A9 b2 j% B4 O+ v
Probabilistic model, 概率模型2 n" Z S' ?: V( g8 k
probability, 概率
! a, Q7 y& k. E7 {Probability density, 概率密度+ E4 W }2 x/ L# m' l
Product moment, 乘积矩/协方差" x6 [# S: `, X1 i/ S( J" w8 b
Profile trace, 截面迹图
; g" G+ L3 p+ S* n' y: KProportion, 比/构成比
, g! K g! I3 }2 I. [3 {* `Proportion allocation in stratified random sampling, 按比例分层随机抽样 x1 a& L8 y r1 n+ f$ r, V3 z1 y
Proportionate, 成比例
& Z& p3 S4 Q9 j1 A6 j* lProportionate sub-class numbers, 成比例次级组含量( n1 P7 z" S, Q, [
Prospective study, 前瞻性调查3 V# \( w4 e+ ]: ^% S
Proximities, 亲近性 0 O# n1 Q( B1 [5 ~( G% @# D {
Pseudo F test, 近似F检验
8 P4 G) I, c; h& oPseudo model, 近似模型
, A6 X, r! _ p* R- {Pseudosigma, 伪标准差
9 k @6 `$ C4 i8 u0 j5 v w& C9 c# mPurposive sampling, 有目的抽样
, \: S- e! S. O& h. rQR decomposition, QR分解
! \8 H1 E* T! k% ?& `Quadratic approximation, 二次近似
! h; _! x1 w: G8 bQualitative classification, 属性分类. h2 t! k ~. E- F
Qualitative method, 定性方法: P& m/ M8 O; k/ a- A# P
Quantile-quantile plot, 分位数-分位数图/Q-Q图, b* J/ A H9 B# Y
Quantitative analysis, 定量分析2 |; A L" D2 }" g$ P
Quartile, 四分位数7 s: t$ N* K' G6 ]) j/ R
Quick Cluster, 快速聚类) }( B2 m- Z' w! p
Radix sort, 基数排序- ~4 r" q9 X% l! C& T
Random allocation, 随机化分组
- j+ R8 w t( [6 b# s" rRandom blocks design, 随机区组设计
8 n% U0 Z( X* y& h0 f5 _* _! qRandom event, 随机事件, ]* G: f# B# C$ }
Randomization, 随机化
$ ^' @: g6 r: _( J+ q: ERange, 极差/全距
- i; M1 L4 j% `- A+ c" J6 PRank correlation, 等级相关4 A# e5 b7 e7 Q! G
Rank sum test, 秩和检验
* H7 L% w4 s$ W* q; U4 o& xRank test, 秩检验- U& P) V6 p( ]) x! p1 P" a0 F0 }
Ranked data, 等级资料
1 x4 _% ^. N5 c- C4 R6 h( iRate, 比率
6 {* M! U: I5 Y2 e' A0 kRatio, 比例6 I/ w: P* j5 R- p! j1 U7 i4 @
Raw data, 原始资料
2 N+ g( Q6 K- M6 nRaw residual, 原始残差
! g3 {4 {1 k; R* H- [- hRayleigh's test, 雷氏检验' P% K7 h* ^# ^9 y
Rayleigh's Z, 雷氏Z值
2 j0 ]6 t8 U1 e# X" S7 e2 \6 FReciprocal, 倒数: n% K& ~# V5 E k
Reciprocal transformation, 倒数变换
, ~4 M" `$ A" i. {/ |1 yRecording, 记录
0 r$ L' ]* j) b, X' v! u2 tRedescending estimators, 回降估计量) s6 O9 p1 F( x* z" z
Reducing dimensions, 降维
2 D5 l( l& g# O x# d; B7 rRe-expression, 重新表达; h& Y# i7 ~- r" `6 ~/ E6 S
Reference set, 标准组5 E! L5 b& i- ~; U0 q Y9 S
Region of acceptance, 接受域
) t0 }1 t2 h' j6 A2 X% `3 eRegression coefficient, 回归系数. Z- r8 a6 w8 Y% R( I
Regression sum of square, 回归平方和
# u2 i6 W$ H+ c' g& i9 Y9 LRejection point, 拒绝点
6 P+ u: b+ f f( t5 k, FRelative dispersion, 相对离散度
; t8 C( U0 U7 \Relative number, 相对数
8 k! e7 l- v1 \$ K& \Reliability, 可靠性
, j7 _( F. A: ]7 ~1 g8 rReparametrization, 重新设置参数0 ]7 W. n+ G$ q- z0 l2 r
Replication, 重复
$ l X/ R" X. l0 N; Z/ RReport Summaries, 报告摘要
J( ^! v; `* F+ A4 xResidual sum of square, 剩余平方和
; o" @) Z1 x, ?6 n4 {Resistance, 耐抗性
% _0 w$ B8 L! p0 ]4 {) B. j' BResistant line, 耐抗线. P7 W, D/ O, Y
Resistant technique, 耐抗技术
+ F- y U Z1 f/ bR-estimator of location, 位置R估计量
4 D* I0 r) e! g: Q' q2 U9 E6 _R-estimator of scale, 尺度R估计量
+ u7 n/ l3 W* g9 pRetrospective study, 回顾性调查
9 n/ O& C% g0 [. x1 V% aRidge trace, 岭迹
+ N# } ]4 Z; z; S4 QRidit analysis, Ridit分析
* U I: k9 E4 m0 d% V; c" D% K8 qRotation, 旋转
* x- j f' H) q1 Y" ~, NRounding, 舍入
7 B1 E+ n- r3 E; Q: @Row, 行& s) N& A: V" } p7 L& [
Row effects, 行效应# a$ [2 t/ r7 s; D4 M" N5 o% I! G
Row factor, 行因素" T1 [: C% V6 T7 h' r! `* R
RXC table, RXC表
: K+ w" d0 J! V, i! cSample, 样本. Z# R7 p5 ~4 m& e: v( B4 B- R
Sample regression coefficient, 样本回归系数
1 r3 x. _; x9 e% j* i; M& sSample size, 样本量
" B$ \* j+ `3 jSample standard deviation, 样本标准差- {4 y+ q' v1 Q# r
Sampling error, 抽样误差& j, ~$ h$ h J3 S I
SAS(Statistical analysis system ), SAS统计软件包- N6 s9 X: a% d1 i( o
Scale, 尺度/量表2 a5 s# V9 P/ w+ U
Scatter diagram, 散点图# u% s5 X. M3 Y0 D" H
Schematic plot, 示意图/简图 W. r/ h9 n! Y. U. ?7 n$ c
Score test, 计分检验0 t8 x' F$ m% l( s3 S( n+ K
Screening, 筛检0 m# a8 D5 |, ?# R/ L6 y
SEASON, 季节分析
j d- S* F( H/ eSecond derivative, 二阶导数
6 _; b0 R- e% o* M Q- u' eSecond principal component, 第二主成分6 S. h- K$ [/ Z7 o- u
SEM (Structural equation modeling), 结构化方程模型
. K& V X5 {0 v% J6 KSemi-logarithmic graph, 半对数图
5 ]$ Y+ o' T4 \ ASemi-logarithmic paper, 半对数格纸* m# w4 ?* x: b" N8 M, g
Sensitivity curve, 敏感度曲线% \& n1 ?8 p: b
Sequential analysis, 贯序分析3 r$ q1 r' y/ ?3 L* t
Sequential data set, 顺序数据集
) W* o, b- a! K# V5 Y( ?, Q/ W" pSequential design, 贯序设计8 o; f& g1 R4 n( s) Q. h5 J3 E
Sequential method, 贯序法- @ c. R, Z9 p
Sequential test, 贯序检验法5 [2 {: q( ~4 f- ?6 n
Serial tests, 系列试验
: u3 Y% x+ r5 ~" DShort-cut method, 简捷法 m, C: `6 q R4 \7 H! y
Sigmoid curve, S形曲线3 i1 s* G: u& ~. J
Sign function, 正负号函数; V8 h% G2 f! ?! Y4 ~+ m
Sign test, 符号检验( ~* P" |' i+ J2 B* g& O
Signed rank, 符号秩' j& Y: Q( T2 G4 `5 E, w
Significance test, 显著性检验- M3 p0 G% B2 F$ j
Significant figure, 有效数字; [9 w' V' C7 O3 d; x( L; K
Simple cluster sampling, 简单整群抽样' F- ]7 e" ] ]* |& {. @' l
Simple correlation, 简单相关. ?& T+ |: {/ [/ J- I! }9 K/ o
Simple random sampling, 简单随机抽样
9 }* f% h8 Y, h$ s9 P1 s0 bSimple regression, 简单回归
$ P- H$ T' ]- I( Q' C4 @% n5 Fsimple table, 简单表4 b: Q2 ^+ T6 H2 G. \$ L" Y' v
Sine estimator, 正弦估计量
V* H5 [- O0 L; {) |/ k; n% f8 DSingle-valued estimate, 单值估计8 j/ |0 r0 U' D! Q+ i4 K
Singular matrix, 奇异矩阵
2 @/ L) d8 E9 {0 u' v7 P2 aSkewed distribution, 偏斜分布
: Q5 ?0 D7 G wSkewness, 偏度
" n6 ]. @% [9 `& [" a6 }Slash distribution, 斜线分布$ ?7 l! B! K7 w( a2 n8 X% D
Slope, 斜率
& ?7 J+ c2 ]6 N* ~( z# @, d NSmirnov test, 斯米尔诺夫检验
4 {7 C$ ^2 t: [& q7 E# k* h. KSource of variation, 变异来源
/ q, t/ X7 z, v3 o0 RSpearman rank correlation, 斯皮尔曼等级相关
7 `5 s0 U3 R4 W0 ^6 oSpecific factor, 特殊因子
4 F* H7 N+ Z9 eSpecific factor variance, 特殊因子方差
3 |3 ], `, U3 e# J6 rSpectra , 频谱
B8 ^3 @2 n" Y n, T# N- mSpherical distribution, 球型正态分布
0 s; ]0 i/ x$ R+ X. ?( SSpread, 展布# t, C- T" e2 t# |; _( ?
SPSS(Statistical package for the social science), SPSS统计软件包
! a2 A7 G5 ?; v+ x7 v8 iSpurious correlation, 假性相关& \$ `+ }/ T) H/ y
Square root transformation, 平方根变换. u$ E# N3 l0 M9 z# N! g# T% J/ U
Stabilizing variance, 稳定方差
, g# ?; i2 H9 o+ ~( a- LStandard deviation, 标准差
2 e; D( ~1 e% _7 {% M6 PStandard error, 标准误
" F! n. u9 U( H# w4 k rStandard error of difference, 差别的标准误; [( l8 a/ S& v5 |/ H
Standard error of estimate, 标准估计误差: C: D5 _! {5 `6 k7 A
Standard error of rate, 率的标准误
- v# W) @, Q0 d$ J: I; bStandard normal distribution, 标准正态分布6 N/ _ R2 V$ A u+ I
Standardization, 标准化/ a( ~! ~' | _$ w
Starting value, 起始值
+ Z2 N @( n. |! ^Statistic, 统计量0 h( D! k" f+ C% F y1 @# u1 `
Statistical control, 统计控制
, E- v, [8 ~' _# h6 m$ ?8 c9 s- ~Statistical graph, 统计图
+ f9 z& Q8 X T% q- w# D3 E! KStatistical inference, 统计推断
5 K6 ? X0 _" c: OStatistical table, 统计表: v" K! N* ^0 o& n0 y
Steepest descent, 最速下降法# }. v7 Y9 I8 L$ B" P; B
Stem and leaf display, 茎叶图# x# G. x1 y$ Y* x4 R. y! R h
Step factor, 步长因子
3 e3 z- c5 W+ Q; R+ i( xStepwise regression, 逐步回归: g8 E. a4 n1 [7 Z0 T
Storage, 存9 M1 ^$ s7 J, [' h9 a+ A$ `0 C
Strata, 层(复数)
+ j# {2 y! k+ W$ Z8 ^Stratified sampling, 分层抽样
2 l; B8 L* l0 {" p0 Y9 L: oStratified sampling, 分层抽样# N1 s9 ]2 ]7 [6 d7 m# A( `/ W) P
Strength, 强度& W2 e8 j3 I9 I+ z
Stringency, 严密性, a3 G# e6 n6 s3 V
Structural relationship, 结构关系
0 s# y/ y) W' \/ j3 s3 m+ k6 sStudentized residual, 学生化残差/t化残差4 p2 Y, _0 E$ j4 w, ]8 n# w% Y
Sub-class numbers, 次级组含量, n% U6 n& U' S( ~5 o
Subdividing, 分割
$ i( X, X/ c, K. _- c- Y1 SSufficient statistic, 充分统计量4 W% r( B* m3 R* k, o* v1 |4 U- V+ P
Sum of products, 积和
6 Q& N. O. o+ s. qSum of squares, 离差平方和
4 g- }- k* k2 V: SSum of squares about regression, 回归平方和
( D$ C2 ?! [- {& q$ CSum of squares between groups, 组间平方和, I9 S+ Z% b8 ?- A
Sum of squares of partial regression, 偏回归平方和
+ a4 k5 o' r! ^% uSure event, 必然事件
a2 O) a# ?' |$ Z# NSurvey, 调查1 V6 F- Z @3 C0 ]7 c
Survival, 生存分析
b& e, L: `1 e/ f$ L8 aSurvival rate, 生存率
) G% g% |" m" M1 MSuspended root gram, 悬吊根图! ` r" z' _* N9 ^1 `
Symmetry, 对称5 r2 a; G" K0 d' G' J7 s
Systematic error, 系统误差
8 O# @" m; u2 w0 s/ hSystematic sampling, 系统抽样# ~. {$ p0 W1 I$ k/ P( P4 r
Tags, 标签8 Q. Y7 N8 T j4 W3 i! l5 L
Tail area, 尾部面积
" G8 X5 x' f x* p$ Q) ^/ ATail length, 尾长
$ i2 ?4 {4 }/ }' S4 c- X8 rTail weight, 尾重5 w6 S% t" r( w; Y7 A' b
Tangent line, 切线
9 f" ^& P8 J4 t& [0 {Target distribution, 目标分布
$ K! D# D$ X+ ~: X; k- ?Taylor series, 泰勒级数
* N# |7 Z n" r- ^% f( bTendency of dispersion, 离散趋势
6 U5 l+ S; E. X( VTesting of hypotheses, 假设检验; R5 A8 P+ P4 B; ]9 v
Theoretical frequency, 理论频数! s3 j, v0 m1 H& u4 @7 E
Time series, 时间序列
. r9 a& w; ?' l! k* C+ pTolerance interval, 容忍区间
4 O2 c. K) b c6 t4 h B8 E z5 WTolerance lower limit, 容忍下限/ m% ]. q x6 L+ |
Tolerance upper limit, 容忍上限, W/ e5 S6 ^" J7 a% K
Torsion, 扰率0 d5 w+ \* a, t# l1 |* X
Total sum of square, 总平方和 T. v: Y$ m/ ?& n3 c4 a
Total variation, 总变异
5 l* \9 s( A) V, z' ?, W1 GTransformation, 转换
4 s) T' Y n, W& q8 }Treatment, 处理
4 C E% M2 t) J. |Trend, 趋势
o- W* P# a$ | j3 d# ]Trend of percentage, 百分比趋势
: F6 w& t5 _. I; b+ dTrial, 试验8 v3 [% i3 i. R1 T0 V
Trial and error method, 试错法, ^9 ` w# e: ~; ~* z+ Z
Tuning constant, 细调常数8 Z3 V: w) b' x: d
Two sided test, 双向检验8 H* `6 Z3 b* e9 B' y
Two-stage least squares, 二阶最小平方% l% F! R+ w( k3 N+ |
Two-stage sampling, 二阶段抽样
! C4 t$ `4 k/ ~' |$ jTwo-tailed test, 双侧检验
( i- s, J, w2 x. j% YTwo-way analysis of variance, 双因素方差分析7 z' m# @( D# o+ D
Two-way table, 双向表' u% c; z2 c( M; q7 e2 e
Type I error, 一类错误/α错误
0 ?% N' k. a1 E- a' W6 N$ m' {Type II error, 二类错误/β错误
; K ^( G3 T/ T& `( k! e# KUMVU, 方差一致最小无偏估计简称
/ l* H, [: d3 y6 r, h* [& BUnbiased estimate, 无偏估计
& q2 Q3 H% U; b, FUnconstrained nonlinear regression , 无约束非线性回归) m( T7 k( B3 p7 B; i6 X _
Unequal subclass number, 不等次级组含量
! C6 F3 Z/ [% G& r% }3 |% a1 V; _Ungrouped data, 不分组资料3 }1 p/ H( J. d, _* P- g+ H
Uniform coordinate, 均匀坐标9 J. ]3 O* g7 m2 E
Uniform distribution, 均匀分布
) X7 D& l! C, v5 O U; e2 x& _Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
1 B2 G# e7 n. S/ O0 W8 h rUnit, 单元6 n2 d7 y7 T, _& e
Unordered categories, 无序分类
' @% c; w3 D D9 f1 ^Upper limit, 上限
" B+ k9 a* z+ zUpward rank, 升秩, c! t6 b# m6 A& I0 D1 J K
Vague concept, 模糊概念
( J2 v! O5 R: D5 C0 vValidity, 有效性1 F! ~5 A3 ]% L" n9 t+ J" g$ p
VARCOMP (Variance component estimation), 方差元素估计6 I3 |; }8 F6 }, \! n
Variability, 变异性# j, R, g: J, Q+ \
Variable, 变量$ ?, M& d. w2 K$ ^+ h
Variance, 方差+ x0 s, Z% A* j, u5 H
Variation, 变异1 r4 Y1 Q* ^. M
Varimax orthogonal rotation, 方差最大正交旋转
! N F# G0 b2 N- F2 A5 u( K# n8 k1 j, gVolume of distribution, 容积
8 b( y2 ^1 w4 d' O; MW test, W检验
. }+ {" y4 {# ]7 O. T- G/ hWeibull distribution, 威布尔分布
3 x# D: T H( w9 M2 X- `, WWeight, 权数4 p, ?: [3 ?4 K$ \# H; x# X( N
Weighted Chi-square test, 加权卡方检验/Cochran检验0 O) O+ v& v' v0 W2 v, t
Weighted linear regression method, 加权直线回归
4 D" N& |' _* zWeighted mean, 加权平均数
3 S/ Q) c, Z6 m; b& _$ ~1 KWeighted mean square, 加权平均方差7 Z/ Q# I' I6 u% O/ `; D
Weighted sum of square, 加权平方和
. c! U) ^" }1 @. a4 xWeighting coefficient, 权重系数
& @- g" i1 D- F7 u2 s5 C1 m3 ]Weighting method, 加权法
$ C, g G& m# nW-estimation, W估计量
4 Z. D1 |' q& v$ K l1 @6 RW-estimation of location, 位置W估计量' U/ v% ]; Z2 U# j
Width, 宽度- `' d: }. i1 J( r4 h& W
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
* M" |- `+ X# |& IWild point, 野点/狂点/ c7 T7 C' e" F8 N7 M x4 o7 d
Wild value, 野值/狂值
- n& i8 | I5 L! |! g$ T' |( W8 aWinsorized mean, 缩尾均值
5 }+ C; ~( t, a& R. ^/ x; PWithdraw, 失访
# k1 `8 V9 t' S# b/ Y% \! ZYouden's index, 尤登指数
) X( O7 N# j0 M1 B2 S0 G$ O1 tZ test, Z检验. j; O7 E6 s# A/ k7 J+ U/ F2 E$ G$ G
Zero correlation, 零相关
" @- I( a. I. [" `% HZ-transformation, Z变换 |
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